An Evolutionary Algorithm for Global Optimization Based on Level-Set Evolution and Latin Squares

• Published in: IEEE transactions on evolutionary computation Vol. 11; no. 5; pp. 579 - 595
• Main Authors: Wang, Yuping, Dang, Chuangyin
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.10.2007; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Algorithms; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Computer simulation; Crossovers; Design optimization; Evolutionary algorithm (EA); Evolutionary algorithms; Evolutionary computation; Exact sciences and technology; Genetic mutations; global optimization; Latin squares; Learning and adaptive systems; Level set; level-set evolution; Mathematical analysis; Mathematical models; Monte Carlo methods; Numerical simulation; Operators; Optimization; Scattering; Space exploration; Studies; Testing; Monte Carlo method; Probabilistic approach; Information system; Evolutionary algorithm (EA); Evolutionary algorithm; Contour line; Global optimum; Mean value; Modeling; global optimization; Image segmentation; level-set evolution; Genetic algorithm; Optimal solution; Latin squares; Objective function; Mathematical programming

In this paper, the level-set evolution is exploited in the design of a novel evolutionary algorithm (EA) for global optimization. An application of Latin squares leads to a new and effective crossover operator. This crossover operator can generate a set of uniformly scattered offspring around their...